Preprint
Aug 2026
Improved regret bounds for structured online learning of quantum states
It is shown that exploiting additional structure in the measurements leads to significantly stronger regret guarantees and that one can achieve logarithmic regret, independent of both the number of qubits and measurement outcomes, for multi-outcome measurements under squared $L_2$ loss.
Akshay Bansal, Jiahui Liu
· 0 citations